ORKA 2

Ensemble Methods and Ensemble Models

ORKA 2 – Optimisation of Ensemble Forecasts with Regenerative Inputs for Short-term Forecasts applied to the Example of Grid Security Calculations and Current Carrying Capacity Forecasts.

Based on the results of the project ORKA, ensemble models and methods and are at the center of ORKA 2. Here, the German Weather Service (DWD) and the network operators 50Hertz Transmission GmbH (transmission grid) and TEN Thüringer Energienetze (distribution grid) are to continue working in close cooperation on the improvement of network node predictions and the integration of forecasts into grid operations.

Current Carrying Capacity of Overhead Lines

An important new issue is short-term predictions of the current carrying capacity of overhead lines, which refers to the maximum current without excessive slack or thermal overloading of the conductor. The current carrying capacity of overhead lines is currently rarely used in network operations management. However, as the wind ensures a better cooling of the lines in high wind feed situations, a great potential for the better use of existing network infrastructure for the acceptance of large amounts of renewable electricity can be tapped here, especially in critical situations.

Ensemble Methods and Ensemble Models

In particular, ensemble predictions are especially suited to calculating the probability of exceedance of the maximum current carrying capacity for overhead lines. The ensemble system COSMO-DE-EPS of DWD is used as a basis for this purpose, where it is obviously essential for the ensemble to correctly estimate the prediction uncertainty.

In order to improve this property for the previously mentioned area of application, emphasis is placed on the important prediction variables windspeed, solar power and temperature. Moreover, intensive work is done on the weaknesses of the model during the simulation of boundary layer and irradiation processes, as the prediction quality of the deterministic model used in the ensemble influences the properties of the ensemble.